With the increased availability of parallel computer resources amenable to large scale scientific computing, it is essential to optimize the use of these resources. The efforts include the development of parallel computing techniques suitable for macromolecular simulation and the development of a parallel computer cluster and related software for high-efficiency simulations at low cost. Current projects include: - LoBoS: High performance computing using PC clusters - Development of parallel QM/MM methods - Development and evaluation of parallel algorithms for molecular dynamics - Development and support of parallel CHARMM - Development of Latency-tolerant algorithms for Parallel Computing The LoBoS (Lots of Boxes on Shelves) and LoBoSII supercomputers have been designed and constructed using commodity PCs. They provide a greater than 10-fold improvement in price/performance when compared with the traditional supercomputer vendors offerings. The initial approach taken for LoBoS had been very successful for certain applications with 128 processors and multiple fast Ethernet connections per node. LoBoSII is a substantial improvement in scalability due to a 5-fold improvement in bandwidth using Gigabit Ethernet and customizations of the TCP stack in the Linux kernel have reduced latency by half. LoBoSII has 200 PentiumII/III 450MHz processors, 1.5 Terabytes of disk space and a fully switched Gigabit network. The LoBoS project continues to develop collaborative arrangements through beta- test programs for network switches, interfaces and high-speed storage devices. Cluster management and queuing software supporting features unique to a laboratory-sized cluster has been developed and distributed to several academic sites. The LoBoS Project has produced the most capable computational system at the NIH for most applications involving computational chemistry tools. It has opened up a new realm of high performance computing which continues to drive the cost down while improving reliability through the use of loosely-coupled clusters. The classes of applications that execute efficiently on clusters have been characterized and efforts to support latency-and bandwidth-tolerant algorithms in hardware are under review. - parallel, computing, high performance, CHARMM, LoBoS, molecular dynamics, simulation